A Study of the 16-Plithogenic and 17-Plithogenic Square Real Matrices and Their Properties

Javier; Renatto Oyague; Enrique Condor; Guillermo; Juan Gamarra; Warshine

doi:https://doi.org/10.54216/IJNS.230306

Fusion: Practice and Applications | 2024

Optimal Integration of Data Fusion in Solar Power Analytics: Enhancing Efficiency and Accuracy

At the forefront of sustainable energy solutions lies renewable energy, particularly solar power. Nevertheless, the optimization of solar power systems necessitates comprehensive analytics, especially for proactive maintenance fault anticipation. This research evaluates data fusion techniques using both linear and non-linear regression models for predicting faults in solar power plants. The study begins with careful data preparation processes to ensure clean and harmonized data sets that include irradiation, temperature, historical fault records, and yield. Linear regression techniques provide insights into straightforward correlations while non-linear models go deep into complex relationships within the data. The results indicate positive outcomes demonstrating the potential of these fusion techniques as far as improving accuracy in fault prediction is concerned. These findings highlight the importance of refining data preparation prior to any fusion process and recommend further exploration into more advanced fusion methodologies. This paper helps advance proactive maintenance strategies for solar power plants thereby making this source of energy more dependable and resilient.

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Darío González-Cruz mail -

Franky Jiménez-García mail -

Javier Gamboa-Cruzado mail -

Edward R. Luna Victoria mail -

María Lima Bendezú mail -

Reem Attasi mail

link https://doi.org/10.54216/FPA.140217

Volume & Issue

Vol. Volume 14 / Iss. Issue 2

Details open_in_new

Journal of Intelligent Systems and Internet of Things |

Implementation of Facial Emotion Recognition System using CNN and IoT

A lot of effort has been paid to emotion modelling and recognition by fields including psychology, cognitive science, and, more recently, engineering. While behavioral modalities have been the subject of extensive investigation, physiological signals have received less attention. Electrocardiograph (ECG) signals can vary depending on the emotion, and different emotions can be identified by different changes in ECG signals. The goal of this study is to use ECG signals to recognize emotions. Four different emotions are represented by the data: happy, thrilling, tranquil, and tense. A finite impulse filter is then used to de-noise the raw data. To improve the accuracy of emotion recognition, we utilize the Discrete Cosine Transform (DCT) to extract characteristics from the collected data. Electrocardiograms (ECGs) and GSR are used in this project's emotion recognition research as both a unimodal and multimodal approach to emotion recognition systems. There are critical observations made of the following processes: pre-processing, validation, dimensionality reduction, feature extraction, feature selection, and data collecting. Additionally, this project showcases architectures with accuracy levels greater than 90%. Also evaluated are the existing ECG and GSR inclusive emotional databases, and a popularity analysis is provided. This review also covers the advantages of emotion recognition technologies for healthcare systems. We conclude with a full discussion of the topic and recommendations for future work based on the evaluated literature. The results offered here are helpful for aspiring researchers looking to review the overview of earlier studies on ECG and GSR -based emotion recognition systems, identify knowledge gaps, and develop and design future applications of emotion recognition systems, particularly for enhancing healthcare.

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link

Volume & Issue

Details open_in_new

Journal of Intelligent Systems and Internet of Things |

Implementation of Facial Emotion Recognition System using CNN and IoT

A lot of effort has been paid to emotion modelling and recognition by fields including psychology, cognitive science, and, more recently, engineering. While behavioral modalities have been the subject of extensive investigation, physiological signals have received less attention. Electrocardiograph (ECG) signals can vary depending on the emotion, and different emotions can be identified by different changes in ECG signals. The goal of this study is to use ECG signals to recognize emotions. Four different emotions are represented by the data: happy, thrilling, tranquil, and tense. A finite impulse filter is then used to de-noise the raw data. To improve the accuracy of emotion recognition, we utilize the Discrete Cosine Transform (DCT) to extract characteristics from the collected data. Electrocardiograms (ECGs) and GSR are used in this project's emotion recognition research as both a unimodal and multimodal approach to emotion recognition systems. There are critical observations made of the following processes: pre-processing, validation, dimensionality reduction, feature extraction, feature selection, and data collecting. Additionally, this project showcases architectures with accuracy levels greater than 90%. Also evaluated are the existing ECG and GSR inclusive emotional databases, and a popularity analysis is provided. This review also covers the advantages of emotion recognition technologies for healthcare systems. We conclude with a full discussion of the topic and recommendations for future work based on the evaluated literature. The results offered here are helpful for aspiring researchers looking to review the overview of earlier studies on ECG and GSR -based emotion recognition systems, identify knowledge gaps, and develop and design future applications of emotion recognition systems, particularly for enhancing healthcare.

groups

link

Volume & Issue

Details open_in_new

Fusion: Practice and Applications | 2024

Proposed Framework for Semantic Segmentation of Aerial Hyperspectral Images Using Deep Learning and SVM Approach

The combination of deep neural networks and assistance vector machines for hyperspectral image recognition is presented in this work. A key issue in the real-world hyperspectral imaging system is hyperspectral picture recognition. Although deep learning can replicate highly dimensional feature vectors from source data, it comes at a high cost in terms of time and the Hugh phenomenon. The selection of the kernel feature and limit has a significant impact on the presentation of a kernel-based learning system. We introduce Support Vector Machine (SVM), a kernel learning method that is used to feature vectors obtained from deep learning on hyperspectral images. By modifying the data structure's parameters and kernel functions, the learning system's ability to solve challenging problems is enhanced. The suggested approaches' viability is confirmed by the outcomes of the experiments. At a particular rate, accuracy of testing for classification is around 90%. Moreover, to significantly make framework robust, validation is done using 5-flod verification.

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Saadya Fahad Jabbar mail -

Nuha Sami Mohsin mail -

Bourair Al-Attar mail -

Israa Ibraheem Al_Barazanchi mail

link https://doi.org/10.54216/FPA.140218

Volume & Issue

Vol. Volume 14 / Iss. Issue 2

Details open_in_new

International Journal of Neutrosophic Science | 2024

Neutrosophic Fuzzy Score Matrices: A Robust Framework for Advancing Medical Diagnostics

In this paper, we introduce the Single-Valued Neutrosophic Fuzzy Matrix (SVNFM), which consists of entries that are all single-valued neutrosophic fuzzy sets (SVNFS). Our objective is to provide a practical tool for dealing with uncertain and indeterminate input. To achieve this, we first define a neutrosophic fuzzy matrix (NFM) and discuss its fundamental properties. The use of various operations in decision making is a notable characteristic of single-valued neutrosophic fuzzy matrices (SVNFMs). In this paper, we propose a multicriteria group decision-making method that incorporates novel operations on neutrosophic fuzzy matrices. Finally, we present a case study to demonstrate the effectiveness of the proposed strategy.

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Priya Mathews mail -

Lovelymol Sebastian mail -

Baiju Thankachan mail

link https://doi.org/10.54216/IJNS.230301

Volume & Issue

Vol. Volume 23 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2024

New type of Diophantine neutrosophic aggregation operators and its extension

We introduce the concept of new type of Diophantine neutrosophic set. A Diophatine neutrosophic set is the new type of a neutrosophic set and Diophatine fuzzy set (DioFS). We discuss Diophantine neutrosophic weighted averaging (DioNWA), Diophantine neutrosophic weighted geometric (DioNWG), generalized Diophantine neutrosophic weighted averaging(GDioNWA), generalized Diophantine neutrosophic weighted geometric (GDioNWG). In this article, we define the Euclidean distance (ED), Hamming distance (HD) and operator laws. By analyzing new type of Diophantine neutrosophic set through algebraic operations, we discuss its properties.

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M. Palanikumar mail -

K. Arulmozhi mail -

K. Sundareswari mail -

Aiyared Iampan mail

link https://doi.org/10.54216/IJNS.230302

Volume & Issue

Vol. Volume 23 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2024

Some Operations on Trapezoidal Single Valued Neutrosophic Fuzzy Numbers

Almost all situations that arise in applied mathematics involve uncertainty, inconsistency, and indeterminacy. This can be simultaneously handled by the use of single valued neutrosophic fuzzy sets and single valued neutrosophic fuzzy numbers. In this paper, we propose the operations of addition, subtraction, and scalar  multiplication on trapezoidal single valued neutrosophic fuzzy numbers. We introduce some component-wise interval operations on the union of closed bounded intervals. Then we show how this can be used to perform the proposed operations on trapezoidal single valued neutrosophic fuzzy numbers with the help of finite α− cuts, finite β− cuts, finite γ− cuts, and finite δ− cuts, which we define in this paper itself.

groups

Ligin P. Mathew mail -

Lovelymol Sebastian mail -

Baiju Thankachan mail

link https://doi.org/10.54216/IJNS.230303

Volume & Issue

Vol. Volume 23 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2024

A Specific Category of Harmonic Functions Characterized By A Generalized Komatu Operator in Conjunction With The (R-K) Integral Operator and Applications to Neutrosophic Complex Field

In our work, we introduced a distinct subclass of univalent harmonic functions referred to as a subclass of chiral functions. These functions are defined by combining the generalized Komatu operator with the integral operator (R − K), which has positive coefficients within the unit disc A. Also, we generalize the same subclass into neutrosophic complex numbers. Throughout our investigation, we establish several properties associated with these functions, including coefficient estimates, the convex formula, the integral operator, and the Hadamard product. On the other hand, we present the Neutrosophic convex formula and the neutrosophic integral operator.

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Audy Hatim Saheb mail -

Rafid Habib Buti mail

link https://doi.org/10.54216/IJNS.230304

Volume & Issue

Vol. Volume 23 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2024

Research on the Classification and Application of Physical Education Teaching Mode by Neutrosophic Analytic Hierarchy Process

The goal of this paper is to classify and application of Physical Education (PE). PE growth rapidly these days due to rapid development in information technology. This rapid turn over the sports, training and physical education. So, this paper identifies the application of PE by using the Multi-Criteria Decision Making (MCDM) concept. This problem contains many criteria and sub-criteria. This paper proposed the Analytic Hierarchy Process (AHP) to determine the weights of criteria and sub-criteria. The AHP method was used under a neutrosophic environment to deal with uncertainty in this problem. An example is provided to show the outcomes of the proposed method.

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Javier Gamboa-Cruzado mail -

Eduardo Morante-Palomino mail -

Cristina Alzamora Rivero mail -

María Lima Bendezú mail -

Dante Manuel M. Fernández mail

link https://doi.org/10.54216/IJNS.230305

Volume & Issue

Vol. Volume 23 / Iss. Issue 3

Details open_in_new

International Journal of Neutrosophic Science | 2024